The present invention relates generally to traffic management control, and more particularly to real-time predictive traffic management using virtual lanes.
Traffic management is typically achieved through implementation of traffic patterns based upon historic data. For example, because it is known, as an example, that more vehicles travel north on a particular route during the early morning hours that travel south along the same route, more driving lanes may be allocated for the northbound traffic during those early morning hours. Likewise, if the later afternoon/early evening hours are known to produce heavier vehicle traffic in the southbound lanes than the northbound lanes, more southbound lanes can be allocated to accommodate such increased traffic. The decision for managing the traffic through such lane allocations is entirely static, however, and not based on the real-time assessment of the traffic conditions. Thus, if an event occurs that backs up traffic in the direction where there are fewer lane allocations, it is unlikely that additional lanes can be allocated at that moment the traffic becomes congested.
In addition to the static nature of the traffic management, drivers of vehicles are given little to no information for purposes of taking alternate routes should one such alternative become favored over a typically more preferred route. Thus, if a driver is taking a first route that happens to be experiencing traffic issues a short distance away, the driver is generally unaware of the forthcoming traffic delays and given an instantaneous option to take an alternate route or to simply use different driving lanes that will be more efficient based on present conditions. While some technologies may provide a driver with data on traffic conditions on a given route at a particular time, they require the driver to take the initiative to seek out such data.
It is a principal object and advantage of the present invention to provide a system that can capture traffic density data generated by road/lane mounted sensors for automated density analysis and traffic management.
It is another object and advantage of the present invention to provide a system that can perform traffic route optimization using predictive traffic flow analytics and allocate lanes in each direction.
It is a further object and advantage of the present invention to provide a system that assists human drivers of vehicles with audio-visual virtual lane imagery based on dynamic allocation of lanes.
It is an added object and advantage of the present invention to provide a system that assists in navigation for a vehicle based on current location and optimal route as determined by remote and centralized traffic control apparatus.
Other objects and advantages of the present invention will in part be obvious and in part appear hereinafter.